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Generalised density forecast combinations

Author

Listed:
  • Kapetanios, G.
  • Mitchell, J.
  • Price, S.
  • Fawcett, N.

Abstract

Density forecast combinations are becoming increasingly popular as a means of improving forecast ‘accuracy’, as measured by a scoring rule. In this paper we generalise this literature by letting the combination weights follow more general schemes. Sieve estimation is used to optimise the score of the generalised density combination where the combination weights depend on the variable one is trying to forecast. Specific attention is paid to the use of piecewise linear weight functions that let the weights vary by region of the density. We analyse these schemes theoretically, in Monte Carlo experiments and in an empirical study. Our results show that the generalised combinations outperform their linear counterparts.

Suggested Citation

  • Kapetanios, G. & Mitchell, J. & Price, S. & Fawcett, N., 2015. "Generalised density forecast combinations," Journal of Econometrics, Elsevier, vol. 188(1), pages 150-165.
    • Handle: RePEc:eee:econom:v:188:y:2015:i:1:p:150-165
    DOI: 10.1016/j.jeconom.2015.02.047
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    More about this item

    Keywords

    Density forecasting; Model combination; Scoring rules;
    All these keywords.

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

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